Preterm infants have maturational delays in several neurobehavioral systems. This study assesses the impact of the Family Nurture Intervention (FNI) in the neonatal intensive care unit (NICU) on the maturation of autonomic regulation of preterm infants. Preterm infants born at 26–34 weeks postmenstrual age (PMA) were assigned to groups receiving either standard care (SC) or SC plus FNI, using a randomized controlled trial design. At two collection time points, approximately 35 weeks and 41 weeks PMA, electrocardiograms (ECG) were monitored for approximately 1 hour during sleep. Heart rate and respiratory sinus arrhythmia (RSA) were quantified from the ECG. Across the two time points, the FNI group exhibited greater increases in RSA (Cohen's d = 0.35) and slope between RSA and heart rate, as a measure of vagal efficiency (Cohen's d = 0.62). These results document that FNI resulted in enhanced autonomic regulation consistent with greater maturation of cardiac function. These and previous findings strongly suggest that facilitating early nurturing interactions and emotional connection between preterm infants and their mothers is a practicable and effective means of optimizing postnatal development in preterm infants. Interpretation of these autonomic function results also enriches our understanding of the potential long‐term beneficial outcomes of FNI by drawing upon polyvagal theory, which explains how autonomic state provides a neurophysiological platform for optimal co‐regulation between infant and caregiver, and by drawing upon calming cycle theory, which provides a model for understanding how repeated mother/infant calming interactions positively condition autonomic state and reinforce approach, prosocial behaviors.

The evolution of the autonomic nervous system provides an organizing principle to interpret the adaptive significance of physiological systems in promoting social behavior and responding to social challenges. This phylogenetic shift in neural regulation of the autonomic nervous system in mammals has produced a neuroanatomically integrated social engagement system, including neural mechanisms that regulate both cardiac vagal tone and muscles involved in vocalization. Mammalian vocalizations are part of a conspecific social communication system, with several mammalian species modulating acoustic features of vocalizations to signal affective state. Prosody, defined by variations in rhythm and pitch, is a feature of mammalian vocalizations that communicate emotion and affective state. While the covariation between physiological state and the acoustic frequencies of vocalizations is neurophysiologically based, few studies have investigated the covariation between vocal prosody and autonomic state. In response to this paucity of scientific evidence, the current study explored the utility of vocal prosody as a sensitive index of autonomic activity in human infants during the Still Face challenge. Overall, significant correlations were observed between several acoustic features of the infant vocalizations and autonomic state, demonstrating an association between shorter heart period and reductions in heart period and respiratory sinus arrhythmia following the challenge with the dampening of the modulation of acoustic features (fundamental frequency, variance, 50% bandwidth, and duration) that are perceived as prosody.

BackgroundChronic low back pain (CLBP) is characterized by an alteration in pain processing by the central nervous system that may affect autonomic nervous system (ANS) balance. Heart rate variability (HRV) reflects the balance of parasympathetic and sympathetic ANS activation. In particular, respiratory sinus arrhythmia (RSA) solely reflects parasympathetic input and is reduced in CLBP patients. Yet, it remains unknown if non-invasive brain stimulation can alter ANS balance in CLBP patients.ObjectiveTo evaluate if non-invasive brain stimulation modulates the ANS, we analyzed HRV metrics collected in a previously published study of transcranial alternating current stimulation (tACS) for the modulation of CLBP through enhancing alpha oscillations. We hypothesized that tACS would increase RSA.MethodsA randomized, crossover, double-blind, sham-controlled pilot study was conducted to investigate the effects of 10Hz-tACS on metrics of ANS balance calculated from electrocardiogram (ECG). ECG data were collected for 2 mins before and after 40 mins of 10Hz-tACS or sham stimulation.ResultsThere were no significant changes in RSA or other frequency-domain HRV components from 10Hz-tACS. However, exploratory time-domain HRV analyses revealed a significant increase in the standard deviation of normal intervals between R-peaks (SDNN), a measure of ANS balance, for 10Hz-tACS relative to sham.ConclusionAlthough tACS did not significantly increase RSA, we found in an exploratory analysis that tACS modulated an integrated HRV measure of both ANS branches. These findings support the further study of how the ANS and alpha oscillations interact and are modulated by tACS.ClinicalTrials.govTranscranial Alternating Current Stimulation in Back Pain – Pilot Study, NCT03243084.

Heart rate variability (HRV) is highly non-stationary, even if no perturbing influences can be identified during the recording of the data. The non-stationarity becomes more profound when HRV data are measured in intrinsically non-stationary environments, such as social stress. In general, HRV data measured in such situations are more difficult to analyze than those measured in constant environments. In this paper, we analyze HRV data measured during a social stress test using two multiscale approaches, the adaptive fractal analysis (AFA) and scale-dependent Lyapunov exponent (SDLE), for the purpose of uncovering differences in HRV between chronic fatigue syndrome (CFS) patients and their matched-controls. CFS is a debilitating, heterogeneous illness with no known biomarker. HRV has shown some promise recently as a non-invasive measure of subtle physiological disturbances and trauma that are otherwise difficult to assess. If the HRV in persons with CFS are significantly different from their healthy controls, then certain cardiac irregularities may constitute good candidate biomarkers for CFS. Our multiscale analyses show that there are notable differences in HRV between CFS and their matched controls before a social stress test, but these differences seem to diminish during the test. These analyses illustrate that the two employed multiscale approaches could be useful for the analysis of HRV measured in various environments, both stationary and non-stationary.

Vocalizations serve as a conspecific social communication system among mammals. Modulation of acoustic features embedded within vocalizations is used by several mammalian species to signal whether it is safe or dangerous to approach conspecific and heterospecific mammals. As described by the Polyvagal Theory, the phylogenetic shift in the evolution of mammals involved an adaptive neuroanatomical link between the neural circuits regulating heart rate and the muscles involved in modulating the acoustic features of vocalizations. However, few studies have investigated the covariation between heart rate and the acoustic features of vocalizations. In the current study, we document that specific features of vocalizations covary with heart rate in a highly social and vocal mammal, the prairie vole (Microtus ochrogaster). Findings with the prairie vole illustrate that higher pitch (i.e., fundamental frequency) and less variability in acoustic features of vocalizations (i.e., less vocal prosody) are associated with elevated heart rate. The study provides the first documentation that the acoustic features of prairie vole vocalizations may function as a surrogate index of heart rate.

BackgroundPsychological resilience is critical to minimize the health effects of traumatic events. Trauma may induce a chronic state of hyperarousal, resulting in problems such as anxiety, insomnia, or posttraumatic stress disorder. Mind-body practices, such as relaxation breathing and mindfulness meditation, help to reduce arousal and may reduce the likelihood of such psychological distress. To better understand resilience-building practices, we are conducting the Biofeedback-Assisted Resilience Training (BART) study to evaluate whether the practice of slow, paced breathing with or without heart rate variability biofeedback can be effectively learned via a smartphone app to enhance psychological resilience.ObjectiveOur objective was to conduct a limited, interim review of user interactions and study data on use of the BART resilience training app and demonstrate analyses of real-time sensor-streaming data.MethodsWe developed the BART app to provide paced breathing resilience training, with or without heart rate variability biofeedback, via a self-managed 6-week protocol. The app receives streaming data from a Bluetooth-linked heart rate sensor and displays heart rate variability biofeedback to indicate movement between calmer and stressful states. To evaluate the app, a population of military personnel, veterans, and civilian first responders used the app for 6 weeks of resilience training. We analyzed app usage and heart rate variability measures during rest, cognitive stress, and paced breathing. Currently released for the BART research study, the BART app is being used to collect self-reported survey and heart rate sensor data for comparative evaluation of paced breathing relaxation training with and without heart rate variability biofeedback.ResultsTo date, we have analyzed the results of 328 participants who began using the BART app for 6 weeks of stress relaxation training via a self-managed protocol. Of these, 207 (63.1%) followed the app-directed procedures and completed the training regimen. Our review of adherence to protocol and app-calculated heart rate variability measures indicated that the BART app acquired high-quality data for evaluating self-managed stress relaxation training programs.ConclusionsThe BART app acquired high-quality data for studying changes in psychophysiological stress according to mind-body activity states, including conditions of rest, cognitive stress, and slow, paced breathing.

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Heart rate variability (HRV) is a reliable indicator of health status and a sensitive index of autonomic stress reactivity. Stress negatively affects physical and psychological wellness by decreasing cardiovascular health and reducing quality of life. Wearable sensors have made it possible to track HRV during daily activity, and recent advances in mobile technology have reduced the cost and difficulty of applying this powerful technique. Although advances have made sensors smaller and lighter, some burden on the subject remains. Chest-worn electrocardiogram (ECG) sensors provide the optimal source signal for HRV analysis, but they require obtrusive electrode or conductive material adherence. A less invasive surrogate of HRV can be derived from the arterial pulse obtained using the photoplethysmogram (PPG), but sensor placement requirements limit the application of PPG in field research. Factors including gender, age, height, and weight also affect PPG-HRV level, but PPG-HRV is sufficient to track individual HRV reactions to physical and mental challenges. To overcome the limitations of contact sensors, we developed the PhysioCam (PhyC), a non-contact system capable of measuring arterial pulse with sufficient precision to derive HRV during different challenges. This passive sensor uses an off the shelf digital color video camera to extract arterial pulse from the light reflected from an individual’s face. In this article, we validate this novel non-contact measure against criterion signals (ECG and PPG) in a controlled laboratory setting. Data from 12 subjects are presented under the following physiological conditions: rest, single deep breath and hold, and rapid breathing. The following HRV parameters were validated: interbeat interval (IBI), respiratory sinus arrhythmia (RSA), and low frequency HRV (LF). When testing the PhyC against ECG or PPG: the Bland–Altman plots for the IBIs show no systematic bias; correlation coefficients (all p values < 0.05) comparing ECG to PhyC for IBI and LF approach 1, while RSA correlations average 0.82 across conditions. We discuss future refinements of the HRV metrics derived from the PhyC that will enable this technology to unobtrusively track indicators of health and wellness.